Overview

Dataset statistics

Number of variables35
Number of observations1470
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory402.1 KiB
Average record size in memory280.1 B

Variable types

NUM17
CAT15
BOOL3

Warnings

EmployeeCount has constant value "1470" Constant
Over18 has constant value "1470" Constant
StandardHours has constant value "1470" Constant
MonthlyIncome is highly correlated with JobLevelHigh correlation
JobLevel is highly correlated with MonthlyIncomeHigh correlation
JobRole is highly correlated with DepartmentHigh correlation
Department is highly correlated with JobRoleHigh correlation
EmployeeNumber has unique values Unique
NumCompaniesWorked has 197 (13.4%) zeros Zeros
TrainingTimesLastYear has 54 (3.7%) zeros Zeros
YearsAtCompany has 44 (3.0%) zeros Zeros
YearsInCurrentRole has 244 (16.6%) zeros Zeros
YearsSinceLastPromotion has 581 (39.5%) zeros Zeros
YearsWithCurrManager has 263 (17.9%) zeros Zeros

Reproduction

Analysis started2021-06-13 08:35:37.321862
Analysis finished2021-06-13 08:36:38.314991
Duration1 minute and 0.99 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

Age
Real number (ℝ≥0)

Distinct43
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.92380952
Minimum18
Maximum60
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:38.407602image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile24
Q130
median36
Q343
95-th percentile54
Maximum60
Range42
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.135373489
Coefficient of variation (CV)0.2474114564
Kurtosis-0.4041451372
Mean36.92380952
Median Absolute Deviation (MAD)6
Skewness0.4132863019
Sum54278
Variance83.45504879
MonotocityNot monotonic
2021-06-13T11:36:38.582168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%) 
35785.3%
 
34775.2%
 
31694.7%
 
36694.7%
 
29684.6%
 
32614.1%
 
30604.1%
 
33583.9%
 
38583.9%
 
40573.9%
 
Other values (33)81555.4%
 
ValueCountFrequency (%) 
1880.5%
 
1990.6%
 
20110.7%
 
21130.9%
 
22161.1%
 
ValueCountFrequency (%) 
6050.3%
 
59100.7%
 
58141.0%
 
5740.3%
 
56141.0%
 

Attrition
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
No
1233 
Yes
237 
ValueCountFrequency (%) 
No123383.9%
 
Yes23716.1%
 
2021-06-13T11:36:38.699832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

BusinessTravel
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Travel_Rarely
1043 
Travel_Frequently
277 
Non-Travel
150 
ValueCountFrequency (%) 
Travel_Rarely104371.0%
 
Travel_Frequently27718.8%
 
Non-Travel15010.2%
 
2021-06-13T11:36:38.802162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:38.897018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:39.014682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length13
Mean length13.44761905
Min length10

DailyRate
Real number (ℝ≥0)

Distinct886
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean802.4857143
Minimum102
Maximum1499
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:39.177912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile165.35
Q1465
median802
Q31157
95-th percentile1424.1
Maximum1499
Range1397
Interquartile range (IQR)692

Descriptive statistics

Standard deviation403.5090999
Coefficient of variation (CV)0.5028240288
Kurtosis-1.203822808
Mean802.4857143
Median Absolute Deviation (MAD)344
Skewness-0.003518568352
Sum1179654
Variance162819.5937
MonotocityNot monotonic
2021-06-13T11:36:39.355536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
69160.4%
 
108250.3%
 
32950.3%
 
132950.3%
 
53050.3%
 
40850.3%
 
71540.3%
 
58940.3%
 
90640.3%
 
35040.3%
 
Other values (876)142396.8%
 
ValueCountFrequency (%) 
10210.1%
 
10310.1%
 
10410.1%
 
10510.1%
 
10610.1%
 
ValueCountFrequency (%) 
149910.1%
 
149810.1%
 
149620.1%
 
149530.2%
 
149210.1%
 

Department
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Research & Development
961 
Sales
446 
Human Resources
 
63
ValueCountFrequency (%) 
Research & Development96165.4%
 
Sales44630.3%
 
Human Resources634.3%
 
2021-06-13T11:36:39.530930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:39.618128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:39.738258image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length22
Mean length16.54217687
Min length5

DistanceFromHome
Real number (ℝ≥0)

Distinct29
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.192517007
Minimum1
Maximum29
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:39.888442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median7
Q314
95-th percentile26
Maximum29
Range28
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.106864436
Coefficient of variation (CV)0.8818982254
Kurtosis-0.2248334049
Mean9.192517007
Median Absolute Deviation (MAD)5
Skewness0.9581179957
Sum13513
Variance65.72125098
MonotocityNot monotonic
2021-06-13T11:36:40.038034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%) 
221114.4%
 
120814.1%
 
10865.9%
 
9855.8%
 
3845.7%
 
7845.7%
 
8805.4%
 
5654.4%
 
4644.4%
 
6594.0%
 
Other values (19)44430.2%
 
ValueCountFrequency (%) 
120814.1%
 
221114.4%
 
3845.7%
 
4644.4%
 
5654.4%
 
ValueCountFrequency (%) 
29271.8%
 
28231.6%
 
27120.8%
 
26251.7%
 
25251.7%
 

Education
Real number (ℝ≥0)

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.91292517
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:40.185412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.024164945
Coefficient of variation (CV)0.3515932902
Kurtosis-0.5591149664
Mean2.91292517
Median Absolute Deviation (MAD)1
Skewness-0.289681082
Sum4282
Variance1.048913834
MonotocityNot monotonic
2021-06-13T11:36:40.311180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
357238.9%
 
439827.1%
 
228219.2%
 
117011.6%
 
5483.3%
 
ValueCountFrequency (%) 
117011.6%
 
228219.2%
 
357238.9%
 
439827.1%
 
5483.3%
 
ValueCountFrequency (%) 
5483.3%
 
439827.1%
 
357238.9%
 
228219.2%
 
117011.6%
 

EducationField
Categorical

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Life Sciences
606 
Medical
464 
Marketing
159 
Technical Degree
132 
Other
82 
ValueCountFrequency (%) 
Life Sciences60641.2%
 
Medical46431.6%
 
Marketing15910.8%
 
Technical Degree1329.0%
 
Other825.6%
 
Human Resources271.8%
 
2021-06-13T11:36:40.476339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:40.582138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:40.732735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length16
Median length13
Mean length10.53333333
Min length5

EmployeeCount
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
1
1470 
ValueCountFrequency (%) 
11470100.0%
 
2021-06-13T11:36:40.823930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

EmployeeNumber
Real number (ℝ≥0)

UNIQUE

Distinct1470
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1024.865306
Minimum1
Maximum2068
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:40.935685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile96.45
Q1491.25
median1020.5
Q31555.75
95-th percentile1967.55
Maximum2068
Range2067
Interquartile range (IQR)1064.5

Descriptive statistics

Standard deviation602.0243348
Coefficient of variation (CV)0.5874180063
Kurtosis-1.223178906
Mean1024.865306
Median Absolute Deviation (MAD)533.5
Skewness0.01657401958
Sum1506552
Variance362433.2997
MonotocityStrictly increasing
2021-06-13T11:36:41.105664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
204610.1%
 
64110.1%
 
64410.1%
 
64510.1%
 
64710.1%
 
64810.1%
 
64910.1%
 
65010.1%
 
65210.1%
 
65310.1%
 
Other values (1460)146099.3%
 
ValueCountFrequency (%) 
110.1%
 
210.1%
 
410.1%
 
510.1%
 
710.1%
 
ValueCountFrequency (%) 
206810.1%
 
206510.1%
 
206410.1%
 
206210.1%
 
206110.1%
 
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
3
453 
4
446 
2
287 
1
284 
ValueCountFrequency (%) 
345330.8%
 
444630.3%
 
228719.5%
 
128419.3%
 
2021-06-13T11:36:41.277690image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:41.382853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:41.501103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Gender
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Male
882 
Female
588 
ValueCountFrequency (%) 
Male88260.0%
 
Female58840.0%
 
2021-06-13T11:36:41.634091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:41.724022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:41.832896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length4
Mean length4.8
Min length4

HourlyRate
Real number (ℝ≥0)

Distinct71
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65.89115646
Minimum30
Maximum100
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:42.000418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile33
Q148
median66
Q383.75
95-th percentile97
Maximum100
Range70
Interquartile range (IQR)35.75

Descriptive statistics

Standard deviation20.32942759
Coefficient of variation (CV)0.3085304415
Kurtosis-1.196398456
Mean65.89115646
Median Absolute Deviation (MAD)18
Skewness-0.0323109529
Sum96860
Variance413.2856263
MonotocityNot monotonic
2021-06-13T11:36:42.195702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
66292.0%
 
42281.9%
 
98281.9%
 
48281.9%
 
84281.9%
 
79271.8%
 
96271.8%
 
57271.8%
 
52261.8%
 
87261.8%
 
Other values (61)119681.4%
 
ValueCountFrequency (%) 
30191.3%
 
31151.0%
 
32241.6%
 
33191.3%
 
34120.8%
 
ValueCountFrequency (%) 
100191.3%
 
99201.4%
 
98281.9%
 
97211.4%
 
96271.8%
 

JobInvolvement
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
3
868 
2
375 
4
144 
1
 
83
ValueCountFrequency (%) 
386859.0%
 
237525.5%
 
41449.8%
 
1835.6%
 
2021-06-13T11:36:42.396827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:42.515509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:42.640941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

JobLevel
Real number (ℝ≥0)

HIGH CORRELATION

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.063945578
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:42.769811image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.106939899
Coefficient of variation (CV)0.5363222319
Kurtosis0.3991520554
Mean2.063945578
Median Absolute Deviation (MAD)1
Skewness1.025401283
Sum3034
Variance1.22531594
MonotocityNot monotonic
2021-06-13T11:36:42.905655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
154336.9%
 
253436.3%
 
321814.8%
 
41067.2%
 
5694.7%
 
ValueCountFrequency (%) 
154336.9%
 
253436.3%
 
321814.8%
 
41067.2%
 
5694.7%
 
ValueCountFrequency (%) 
5694.7%
 
41067.2%
 
321814.8%
 
253436.3%
 
154336.9%
 

JobRole
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Sales Executive
326 
Research Scientist
292 
Laboratory Technician
259 
Manufacturing Director
145 
Healthcare Representative
131 
Other values (4)
317 
ValueCountFrequency (%) 
Sales Executive32622.2%
 
Research Scientist29219.9%
 
Laboratory Technician25917.6%
 
Manufacturing Director1459.9%
 
Healthcare Representative1318.9%
 
Manager1026.9%
 
Sales Representative835.6%
 
Research Director805.4%
 
Human Resources523.5%
 
2021-06-13T11:36:43.077443image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:43.192363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:43.399075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length25
Median length18
Mean length18.0707483
Min length7

JobSatisfaction
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
4
459 
3
442 
1
289 
2
280 
ValueCountFrequency (%) 
445931.2%
 
344230.1%
 
128919.7%
 
228019.0%
 
2021-06-13T11:36:43.570840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:43.682951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:43.799285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

MaritalStatus
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Married
673 
Single
470 
Divorced
327 
ValueCountFrequency (%) 
Married67345.8%
 
Single47032.0%
 
Divorced32722.2%
 
2021-06-13T11:36:44.312490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:44.406506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:44.532480image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length7
Mean length6.902721088
Min length6

MonthlyIncome
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1349
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6502.931293
Minimum1009
Maximum19999
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:44.700499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1009
5-th percentile2097.9
Q12911
median4919
Q38379
95-th percentile17821.35
Maximum19999
Range18990
Interquartile range (IQR)5468

Descriptive statistics

Standard deviation4707.956783
Coefficient of variation (CV)0.7239745541
Kurtosis1.005232691
Mean6502.931293
Median Absolute Deviation (MAD)2199
Skewness1.369816681
Sum9559309
Variance22164857.07
MonotocityNot monotonic
2021-06-13T11:36:44.880886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
234240.3%
 
556230.2%
 
274130.2%
 
245130.2%
 
261030.2%
 
238030.2%
 
614230.2%
 
634730.2%
 
255930.2%
 
240430.2%
 
Other values (1339)143997.9%
 
ValueCountFrequency (%) 
100910.1%
 
105110.1%
 
105210.1%
 
108110.1%
 
109110.1%
 
ValueCountFrequency (%) 
1999910.1%
 
1997310.1%
 
1994310.1%
 
1992610.1%
 
1985910.1%
 

MonthlyRate
Real number (ℝ≥0)

Distinct1427
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14313.1034
Minimum2094
Maximum26999
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:45.070271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2094
5-th percentile3384.55
Q18047
median14235.5
Q320461.5
95-th percentile25431.9
Maximum26999
Range24905
Interquartile range (IQR)12414.5

Descriptive statistics

Standard deviation7117.786044
Coefficient of variation (CV)0.4972915967
Kurtosis-1.2149561
Mean14313.1034
Median Absolute Deviation (MAD)6206.5
Skewness0.01857780789
Sum21040262
Variance50662878.17
MonotocityNot monotonic
2021-06-13T11:36:45.257256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
422330.2%
 
915030.2%
 
667020.1%
 
732420.1%
 
465820.1%
 
2153420.1%
 
1615420.1%
 
1300820.1%
 
1235520.1%
 
606920.1%
 
Other values (1417)144898.5%
 
ValueCountFrequency (%) 
209410.1%
 
209710.1%
 
210410.1%
 
211210.1%
 
212210.1%
 
ValueCountFrequency (%) 
2699910.1%
 
2699710.1%
 
2696810.1%
 
2695910.1%
 
2695610.1%
 

NumCompaniesWorked
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.693197279
Minimum0
Maximum9
Zeros197
Zeros (%)13.4%
Memory size11.5 KiB
2021-06-13T11:36:45.410790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q34
95-th percentile8
Maximum9
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.498009006
Coefficient of variation (CV)0.9275254455
Kurtosis0.01021381669
Mean2.693197279
Median Absolute Deviation (MAD)1
Skewness1.026471112
Sum3959
Variance6.240048994
MonotocityNot monotonic
2021-06-13T11:36:45.526855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
152135.4%
 
019713.4%
 
315910.8%
 
21469.9%
 
41399.5%
 
7745.0%
 
6704.8%
 
5634.3%
 
9523.5%
 
8493.3%
 
ValueCountFrequency (%) 
019713.4%
 
152135.4%
 
21469.9%
 
315910.8%
 
41399.5%
 
ValueCountFrequency (%) 
9523.5%
 
8493.3%
 
7745.0%
 
6704.8%
 
5634.3%
 

Over18
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
Y
1470 
ValueCountFrequency (%) 
Y1470100.0%
 
2021-06-13T11:36:45.658718image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:45.746399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:45.833503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

OverTime
Boolean

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
No
1054 
Yes
416 
ValueCountFrequency (%) 
No105471.7%
 
Yes41628.3%
 
2021-06-13T11:36:45.923173image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

PercentSalaryHike
Real number (ℝ≥0)

Distinct15
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.20952381
Minimum11
Maximum25
Zeros0
Zeros (%)0.0%
Memory size11.5 KiB
2021-06-13T11:36:46.009181image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q112
median14
Q318
95-th percentile22
Maximum25
Range14
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.659937717
Coefficient of variation (CV)0.2406346025
Kurtosis-0.3005982221
Mean15.20952381
Median Absolute Deviation (MAD)2
Skewness0.8211279756
Sum22358
Variance13.39514409
MonotocityNot monotonic
2021-06-13T11:36:46.136230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
1121014.3%
 
1320914.2%
 
1420113.7%
 
1219813.5%
 
151016.9%
 
18896.1%
 
17825.6%
 
16785.3%
 
19765.2%
 
22563.8%
 
Other values (5)17011.6%
 
ValueCountFrequency (%) 
1121014.3%
 
1219813.5%
 
1320914.2%
 
1420113.7%
 
151016.9%
 
ValueCountFrequency (%) 
25181.2%
 
24211.4%
 
23281.9%
 
22563.8%
 
21483.3%
 
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
3
1244 
4
226 
ValueCountFrequency (%) 
3124484.6%
 
422615.4%
 
2021-06-13T11:36:46.286711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:46.377345image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:46.475419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1
Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
3
459 
4
432 
2
303 
1
276 
ValueCountFrequency (%) 
345931.2%
 
443229.4%
 
230320.6%
 
127618.8%
 
2021-06-13T11:36:46.625794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:46.734737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:46.854464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

StandardHours
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
80
1470 
ValueCountFrequency (%) 
801470100.0%
 
2021-06-13T11:36:46.989607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:47.078663image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:47.167912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length2
Median length2
Mean length2
Min length2

StockOptionLevel
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
0
631 
1
596 
2
158 
3
85 
ValueCountFrequency (%) 
063142.9%
 
159640.5%
 
215810.7%
 
3855.8%
 
2021-06-13T11:36:47.318259image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:47.421870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:47.538812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

TotalWorkingYears
Real number (ℝ≥0)

Distinct40
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.27959184
Minimum0
Maximum40
Zeros11
Zeros (%)0.7%
Memory size11.5 KiB
2021-06-13T11:36:47.685937image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median10
Q315
95-th percentile28
Maximum40
Range40
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.780781676
Coefficient of variation (CV)0.6898105701
Kurtosis0.9182695366
Mean11.27959184
Median Absolute Deviation (MAD)4
Skewness1.117171853
Sum16581
Variance60.54056348
MonotocityNot monotonic
2021-06-13T11:36:47.868604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%) 
1020213.7%
 
61258.5%
 
81037.0%
 
9966.5%
 
5886.0%
 
1815.5%
 
7815.5%
 
4634.3%
 
12483.3%
 
3422.9%
 
Other values (30)54136.8%
 
ValueCountFrequency (%) 
0110.7%
 
1815.5%
 
2312.1%
 
3422.9%
 
4634.3%
 
ValueCountFrequency (%) 
4020.1%
 
3810.1%
 
3740.3%
 
3660.4%
 
3530.2%
 

TrainingTimesLastYear
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.799319728
Minimum0
Maximum6
Zeros54
Zeros (%)3.7%
Memory size11.5 KiB
2021-06-13T11:36:48.025085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.289270621
Coefficient of variation (CV)0.4605656896
Kurtosis0.494992986
Mean2.799319728
Median Absolute Deviation (MAD)1
Skewness0.5531241711
Sum4115
Variance1.662218734
MonotocityNot monotonic
2021-06-13T11:36:48.140772image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
254737.2%
 
349133.4%
 
41238.4%
 
51198.1%
 
1714.8%
 
6654.4%
 
0543.7%
 
ValueCountFrequency (%) 
0543.7%
 
1714.8%
 
254737.2%
 
349133.4%
 
41238.4%
 
ValueCountFrequency (%) 
6654.4%
 
51198.1%
 
41238.4%
 
349133.4%
 
254737.2%
 

WorkLifeBalance
Categorical

Distinct4
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size11.5 KiB
3
893 
2
344 
4
153 
1
 
80
ValueCountFrequency (%) 
389360.7%
 
234423.4%
 
415310.4%
 
1805.4%
 
2021-06-13T11:36:48.299383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-06-13T11:36:48.412862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:48.532212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

YearsAtCompany
Real number (ℝ≥0)

ZEROS

Distinct37
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.008163265
Minimum0
Maximum40
Zeros44
Zeros (%)3.0%
Memory size11.5 KiB
2021-06-13T11:36:48.680816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q39
95-th percentile20
Maximum40
Range40
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.126525152
Coefficient of variation (CV)0.8741984056
Kurtosis3.935508756
Mean7.008163265
Median Absolute Deviation (MAD)3
Skewness1.764529454
Sum10302
Variance37.53431044
MonotocityNot monotonic
2021-06-13T11:36:48.841908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%) 
519613.3%
 
117111.6%
 
31288.7%
 
21278.6%
 
101208.2%
 
41107.5%
 
7906.1%
 
9825.6%
 
8805.4%
 
6765.2%
 
Other values (27)29019.7%
 
ValueCountFrequency (%) 
0443.0%
 
117111.6%
 
21278.6%
 
31288.7%
 
41107.5%
 
ValueCountFrequency (%) 
4010.1%
 
3710.1%
 
3620.1%
 
3410.1%
 
3350.3%
 

YearsInCurrentRole
Real number (ℝ≥0)

ZEROS

Distinct19
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.229251701
Minimum0
Maximum18
Zeros244
Zeros (%)16.6%
Memory size11.5 KiB
2021-06-13T11:36:49.000765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q37
95-th percentile11
Maximum18
Range18
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.623137035
Coefficient of variation (CV)0.856685128
Kurtosis0.4774207735
Mean4.229251701
Median Absolute Deviation (MAD)3
Skewness0.9173631563
Sum6217
Variance13.12712197
MonotocityNot monotonic
2021-06-13T11:36:49.142289image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%) 
237225.3%
 
024416.6%
 
722215.1%
 
31359.2%
 
41047.1%
 
8896.1%
 
9674.6%
 
1573.9%
 
6372.5%
 
5362.4%
 
Other values (9)1077.3%
 
ValueCountFrequency (%) 
024416.6%
 
1573.9%
 
237225.3%
 
31359.2%
 
41047.1%
 
ValueCountFrequency (%) 
1820.1%
 
1740.3%
 
1670.5%
 
1580.5%
 
14110.7%
 

YearsSinceLastPromotion
Real number (ℝ≥0)

ZEROS

Distinct16
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.187755102
Minimum0
Maximum15
Zeros581
Zeros (%)39.5%
Memory size11.5 KiB
2021-06-13T11:36:49.290497image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile9
Maximum15
Range15
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.222430279
Coefficient of variation (CV)1.472939213
Kurtosis3.612673115
Mean2.187755102
Median Absolute Deviation (MAD)1
Skewness1.984289983
Sum3216
Variance10.3840569
MonotocityNot monotonic
2021-06-13T11:36:49.423858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
058139.5%
 
135724.3%
 
215910.8%
 
7765.2%
 
4614.1%
 
3523.5%
 
5453.1%
 
6322.2%
 
11241.6%
 
8181.2%
 
Other values (6)654.4%
 
ValueCountFrequency (%) 
058139.5%
 
135724.3%
 
215910.8%
 
3523.5%
 
4614.1%
 
ValueCountFrequency (%) 
15130.9%
 
1490.6%
 
13100.7%
 
12100.7%
 
11241.6%
 

YearsWithCurrManager
Real number (ℝ≥0)

ZEROS

Distinct18
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.123129252
Minimum0
Maximum17
Zeros263
Zeros (%)17.9%
Memory size11.5 KiB
2021-06-13T11:36:49.568263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q37
95-th percentile10
Maximum17
Range17
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.568136121
Coefficient of variation (CV)0.8653951654
Kurtosis0.1710580839
Mean4.123129252
Median Absolute Deviation (MAD)3
Skewness0.833450992
Sum6061
Variance12.73159537
MonotocityNot monotonic
2021-06-13T11:36:49.708290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%) 
234423.4%
 
026317.9%
 
721614.7%
 
31429.7%
 
81077.3%
 
4986.7%
 
1765.2%
 
9644.4%
 
5312.1%
 
6292.0%
 
Other values (8)1006.8%
 
ValueCountFrequency (%) 
026317.9%
 
1765.2%
 
234423.4%
 
31429.7%
 
4986.7%
 
ValueCountFrequency (%) 
1770.5%
 
1620.1%
 
1550.3%
 
1450.3%
 
13141.0%
 

Interactions

2021-06-13T11:35:40.684814image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:40.826394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:41.007651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:41.175220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:41.351839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:41.534324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:41.722530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:41.928208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:42.125526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:42.327054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:42.497305image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:42.832483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:43.079426image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:43.249404image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:43.406890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:43.605169image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:43.787770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:43.953487image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:44.117244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:44.283471image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:44.461719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:44.721962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:44.961582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:45.335636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:45.585659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:45.962054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:46.191042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:46.420550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:46.642600image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:46.833529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:47.006237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:47.207425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:47.423158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:47.662080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:47.929655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:48.140081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:48.319416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:48.546744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:48.732146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:48.893373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:49.071366image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:49.271749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:49.485073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:49.788963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:50.044091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:50.303122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:51.936339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:52.180068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:52.401057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:52.643842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:52.826547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:53.019882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:35:53.205840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2021-06-13T11:36:30.017677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:30.189331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:30.340747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:30.503295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:30.663384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:30.831388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:30.984646image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:31.430263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:31.600321image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:31.767447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:31.922545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:32.075277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:32.235636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:32.401842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:32.560699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:32.727221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:32.890263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:33.061117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:33.235761image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:33.388921image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:33.550596image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:33.715577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:33.885708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:34.039272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:34.205104image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:34.377110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:34.559334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:34.715979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:34.870578image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:35.034018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:35.206069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:35.368506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:35.536584image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:35.711053image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:35.880229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-06-13T11:36:49.902827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-06-13T11:36:50.389980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-06-13T11:36:50.863867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-06-13T11:36:51.361784image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-06-13T11:36:51.831117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-06-13T11:36:36.301914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-06-13T11:36:38.010164image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
041YesTravel_Rarely1102Sales12Life Sciences112Female9432Sales Executive4Single5993194798YYes11318008016405
149NoTravel_Frequently279Research & Development81Life Sciences123Male6122Research Scientist2Married5130249071YNo2344801103310717
237YesTravel_Rarely1373Research & Development22Other144Male9221Laboratory Technician3Single209023966YYes15328007330000
333NoTravel_Frequently1392Research & Development34Life Sciences154Female5631Research Scientist3Married2909231591YYes11338008338730
427NoTravel_Rarely591Research & Development21Medical171Male4031Laboratory Technician2Married3468166329YNo12348016332222
532NoTravel_Frequently1005Research & Development22Life Sciences184Male7931Laboratory Technician4Single3068118640YNo13338008227736
659NoTravel_Rarely1324Research & Development33Medical1103Female8141Laboratory Technician1Married267099644YYes204180312321000
730NoTravel_Rarely1358Research & Development241Life Sciences1114Male6731Laboratory Technician3Divorced2693133351YNo22428011231000
838NoTravel_Frequently216Research & Development233Life Sciences1124Male4423Manufacturing Director3Single952687870YNo214280010239718
936NoTravel_Rarely1299Research & Development273Medical1133Male9432Healthcare Representative3Married5237165776YNo133280217327777

Last rows

AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumberEnvironmentSatisfactionGenderHourlyRateJobInvolvementJobLevelJobRoleJobSatisfactionMaritalStatusMonthlyIncomeMonthlyRateNumCompaniesWorkedOver18OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
146029NoTravel_Rarely468Research & Development284Medical120544Female7321Research Scientist1Single378584891YNo14328005315404
146150YesTravel_Rarely410Sales283Marketing120554Male3923Sales Executive1Divorced10854165864YYes133280120333220
146239NoTravel_Rarely722Sales241Marketing120562Female6024Sales Executive4Married1203188280YNo1131801212220996
146331NoNon-Travel325Research & Development53Medical120572Male7432Manufacturing Director1Single993637870YNo193280010239417
146426NoTravel_Rarely1167Sales53Other120604Female3021Sales Representative3Single2966213780YNo18348005234200
146536NoTravel_Frequently884Research & Development232Medical120613Male4142Laboratory Technician4Married2571122904YNo173380117335203
146639NoTravel_Rarely613Research & Development61Medical120624Male4223Healthcare Representative1Married9991214574YNo15318019537717
146727NoTravel_Rarely155Research & Development43Life Sciences120642Male8742Manufacturing Director2Married614251741YYes20428016036203
146849NoTravel_Frequently1023Sales23Medical120654Male6322Sales Executive2Married5390132432YNo143480017329608
146934NoTravel_Rarely628Research & Development83Medical120682Male8242Laboratory Technician3Married4404102282YNo12318006344312